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Majeed, M.

Publications and source records attributed to Majeed, M..

11 recordsLinked to original sources
bioRxiv2026

Robust and accessible in situ sequencing with an open-source automated sequencer

Targeted in situ sequencing underlies many spatial transcriptomic, barcoded connectomic, and multiplexed perturbation techniques. Each experiment requires many cycles of chemical reactions and imaging that are time-consuming and error-prone to perform manually, and few commercial platforms can sequence highly diverse RNA barcodes in situ at cellular resolution across large tissue sections. Here we present Seq-o-Matic, an open-source automated in situ sequencer built entirely from commercially available components, which integrates fluidics, heated incubation, and imaging of up to three continuous 18 mm x 50 mm areas on standard microscope slides. Relative to manual sequencing, Seq-o-Matic reduced hands-on time 6- to 17.5-fold and total run time about 2.6-fold. Across three runs spanning two mouse strains and a neonatal marmoset, sequencing quality, measured by signal retention, channel specificity, and phasing, was similar to that of four manually sequenced mouse brains. In four mouse hemispheres sequenced in separate runs (two C57BL/6J, one NOD, and one WSB), consensus cell types were present in every brain and corresponded to those of a manually sequenced C57BL/6J brain. Within cortical excitatory neurons, the two C57BL/6J brains were more similar to each other than were brains of different strains, suggesting that technical variation between runs was small relative to strain differences. Seq-o-Matic thus makes consistent, high-throughput in situ sequencing accessible to laboratories without specialized in situ sequencing expertise.

genomics↗
bioRxiv2026

Selective collateralization of transcriptomically distinct neurons organizes visual-stream output from the primary visual cortex

Parallel visual streams segregate information into pathways specialized for distinct computations, but how this segregation is achieved by anatomical segregation of primary visual cortex output remains unclear. This problem is complicated because individual neurons frequently send broadcasting projections to multiple cortical areas, and the target choice depends on both topographical location and molecular identity. Here we developed axonal BARseq2 to jointly map gene expression and high-resolution axonal projections from 1,448 neurons spanning the mouse primary visual cortex (VISp). Axonal BARseq2 recapitulated projection patterns observed by bulk tracing and single-neuron reconstruction, and recovered transcriptomic identities consistent with reference snRNA-seq datasets. Retinotopy strongly predicted projections to individual cortical targets, particularly for areas proximal to VISp, but explained little of which areas are frequently co-innervated. Instead, co-innervation patterns defined three preferential output pathways that largely corresponded to the ventral stream and two subdivisions of the dorsal stream. These pathways were associated with fine-grained transcriptional identities of L4/5 intra-telencephalic neurons, which were further validated with an external MERFISH dataset. Thus, VISp output is organized by two distinct rules: retinotopy constrains where neurons project, whereas cell-type-associated collateralization constrains which targets are co-innervated. This selective broadcasting, in which single neurons reach many higher visual areas in cell-type-specific combinations, could provide an anatomical substrate for visual-stream segregation at the level of VISp output in mice.

neuroscience↗
bioRxiv2026

Conserved and specialized features of thalamocortical wiring revealed by single-cell projection mapping in mouse and marmoset

Across mammals, brain regions can duplicate, expand, and diversify, requiring long-range connectivity to accommodate species-specific specializations while preserving globally ordered wiring. This challenge is especially pronounced in primate thalamocortical circuits, where select cortical fields and their thalamic partners have expanded disproportionately. Although gene expression in the thalamus follows broad and conserved gradients, how thalamocortical projections are organized at single-neuron resolution, and how this organization is reshaped by expansion, remain unknown. Here, we investigate thalamocortical projection organization by in situ sequencing and BARseq projection mapping in marmosets and mice. We profiled the gene expression of 1.5 million marmoset neurons and jointly measured gene expression and cortical projections in 708 marmoset and 1,518 mouse neurons that spanned multiple thalamic nuclei. In both species, projections of individual neurons targeted diverse areas that together spanned a large fraction of the cortex. Comparing projections at the single-neuron level and local neighborhood level revealed that marmoset thalamocortical projections were more spatially segregated, producing a point-to-point architecture. Strikingly, this local specialization coexisted with a conserved gradient that predominated over discrete anatomical borders: In the higher-order sensory thalamus of both species, gene expression and projections varied continuously across nucleus borders, and borders had only a small effect on projections. Furthermore, in both marmoset and mouse, gene expression gradients were associated with the anteroposterior locations of cortical targets. These results reconcile discrete nucleus and gradient-based models of thalamic organization and suggest that primate circuit specialization is superimposed on a conserved molecular-projection gradient.

neuroscience↗
bioRxiv2026

In Silico Identification of Aminoadipate Semialdehyde Synthase (AASS) as a Novel Prognostic Biomarker in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype that lacks effective targeted therapies. This study aimed to identify robust prognostic biomarkers by integrating network biology with machine learning (ML) approaches. TNBC expression cohorts were analysed to identify differentially expressed genes (DEGs) and crucial gene clusters via limma and Weighted Gene Co-expression Network Analysis (WGCNA). In results, 579 DEGs were identified, and network analysis revealed two TNBC-associated modules. Overlapping determined 208 genes enriched in cell-cycle and mitotic-regulation pathways. To identify candidate biomarkers, protein-protein interaction (PPI) networks and ML feature selection techniques, including support vector machine with recursive feature elimination module (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression, were performed. The Kaplan-Meier (KM) analysis revealed AASS and CCNA2 were favourable prognostic markers, whereas CXCL8, SPP1, and CCNB1 were poor prognostic markers. Multi-level validation and immune-subtype analysis were carried out, revealing AASS as a novel TNBC-associated metabolic tumour suppressor.

cancer biology↗
bioRxiv2025

A gene expression atlas of a juvenile nervous system

Although the fundamental architecture of metazoan nervous systems is typically established in the embryo, substantial numbers of neurons are added during post-natal development while existing neurons expand in size, refine connectivity, and undergo additional differentiation. To reveal the underlying molecular determinants of postembryonic neurogenesis and maturation, we have produced gene expression profiles of all neuron types and their progenitors in the first larval stage (L1) of C. elegans. Comparisons of the L1 profile to the embryo and to the later L4 larval stage identified thousands of differentially expressed genes across individual neurons throughout the nervous system. Key neuropeptide signaling networks, for example, are remodeled during larval development. Gene regulatory network analysis revealed potential transcription factors driving the temporal changes in gene expression across the nervous system, including a broad role for the heterochronic transcription factor lin-14. We utilized available connectomic data of juvenile animals in combination with our neuron-specific atlas to identify potential molecular determinants of membrane contact and synaptic connectivity. These expression data are available through a user-friendly interface at CeNGEN.org for independent investigations of the maturation, connectivity and function of a developing nervous system.

neuroscience↗
bioRxiv2025

Integrating bulk and single cell RNA-seq refines transcriptomic profiles of individual C. elegans neurons

Neuron-specific morphology and function are fundamentally tied to differences in gene expression across the nervous system. We previously generated a single cell RNA-seq (scRNA-Seq) dataset for every anatomical neuron class in the C. elegans hermaphrodite. Here we present a complementary set of bulk RNA-seq samples for 52 of the 118 canonical neuron classes in C. elegans. We show that the bulk RNA-seq dataset captures both lowly expressed and noncoding RNAs that are not detected in the scRNA-Seq profile, but also includes false positives due to contamination by other cell types. We present an analytical strategy that integrates the two datasets, preserving both the specificity of scRNA-Seq data and the sensitivity of bulk RNA-Seq. We show that this integrated dataset enhances the sensitivity and accuracy of transcript detection and differential gene analysis. In addition, we show that the bulk RNA-Seq data set detects differentially expressed non-coding RNAs across neuron types, including multiple families of non-polyadenylated transcripts. We propose that our approach provides a new strategy for interrogating gene expression by bridging the gap between bulk and single cell methodologies for transcriptomic studies. We suggest that these datasets advance the goal of delineating the mechanisms that define morphology and connectivity in the nervous system.

genomics↗
bioRxiv2024

Nervous system-wide analysis of all C. elegans cadherins reveals neuron-specific functions across multiple anatomical scales

Differential expression of cell adhesion proteins is a hallmark of cell type diversity across the animal kingdom. Gene family-wide characterization of their organismal expression and function are, however, lacking. We established an atlas of expression of the entire set of 12 cadherin gene family members in the nematode C. elegans, testing the hypothesis that members of this gene family define combinatorial expression codes that may drive nervous system assembly. This atlas reveals differential expression of genomically tagged cadherin genes across neuronal classes, a dichotomy between broadly- and narrowly-expressed cadherins, and several context-dependent temporal transitions in expression across development. Engineered mutant null alleles of cadherins were analyzed for defects in morphology, behavior, neuronal soma positions, neurite neighborhood topology and fasciculation, and localization of synapses in many parts of the nervous system. This analysis revealed a restricted pattern of neuronal differentiation defects at discrete subsets of anatomical scales, including a novel role of cadherins in experience-dependent electrical synapse formation. In total, our analysis results in novel perspectives on cadherin deployment and function.

neuroscience↗
bioRxiv2024

Comparative connectomics of two distantly related nematode species reveals patterns of nervous system evolution

Understanding the evolution of the bilaterian brain requires a detailed exploration of the precise nature of cellular and subcellular differences between related brains. To define the anatomical substrates of evolutionary change in the nervous system, we undertook an electron micrographic reconstruction of the brain of the predatory nematode Pristionchus pacificus. A comparison with the brain of Caenorhabditis elegans, which diverged at least 100 million years ago, reveals a conserved nematode core connectome and a wide range of specific substrates of evolutionary change. These changes include differences in neuronal cell death, neuronal cell position, axo-dendritic projection patterns and many changes in synaptic connectivity of homologous neurons that display no obvious changes in overall neurite morphology and projection patterns. Arguing against specific hot spots of evolutionary change, connectivity differences are distributed throughout the nervous system and extend to glia as well. We observed examples of apparent circuit drift, where changes in morphology and connectivity of a neuron do not appear to alter its behavioral output. In conclusion, our comprehensive comparison of distantly related nematode species provides novel vistas on patterns of conservation as well as the substrates of evolutionary change in the brain that span multiple organizational levels.

neuroscience↗
bioRxiv2024

Experience-dependent, sexually dimorphic synaptic connectivity defined by sex-specific cadherin expression

We describe here the molecular mechanisms by which juvenile experience defines patterns of sexually dimorphic synaptic connectivity in the adult nervous system of the nematode C. elegans. We show that starvation of juvenile males disrupts serotonin- dependent activation of the CREB transcription factor in a nociceptive sensory neuron, PHB. CREB acts through a cascade of transcription factors to control expression of an atypical cadherin protein, FMI-1/Flamingo. During postembryonic development, FMI-1/Flamingo has the capacity to promote and maintain synaptic connectivity of the PHB nociceptive sensory to a command interneuron, AVA, in both sexes, but the serotonin transcriptional regulatory cassette antagonizes FMI-1/Flamingo expression in males, thereby establishing sexually dimorphic connectivity between PHB and AVA. A critical regulatory node in this process is the CREB-target LIN-29, a Zn finger transcription factor which integrates four different layers of information - sexual specificity, past feeding status, time and cell-type specificity. Our findings provide the mechanistic details of how an early juvenile experience defines sexually dimorphic synaptic connectivity.

neuroscience↗
bioRxiv2023

Toolkits for detailed and high-throughput interrogation of synapses in C. elegans

Visualizing synaptic connectivity has traditionally relied on time-consuming electron microscopy-based imaging approaches. To scale the analysis of synaptic connectivity, fluorescent protein-based techniques have been established, ranging from the labeling of specific pre- or postsynaptic components of chemical or electrical synapses to transsynaptic proximity labeling technology such as GRASP and iBLINC. In this paper, we describe WormPsyQi, a generalizable image analysis pipeline that automatically quantifies synaptically localized fluorescent signals in a high-throughput and robust manner, with reduced human bias. We also present a resource of 30 transgenic strains that label chemical or electrical synapses throughout the nervous system of the nematode C. elegans, using CLA-1, RAB-3, GRASP (chemical synapses), or innexin (electrical synapse) reporters. We show that WormPsyQi captures synaptic structures in spite of substantial heterogeneity in neurite morphology, fluorescence signal, and imaging parameters. We use these toolkits to quantify multiple obvious and subtle features of synapses - such as number, size, intensity, and spatial distribution of synapses - in datasets spanning various regions of the nervous system, developmental stages, and sexes. Although the pipeline is described in the context of synapses, it may be utilized for other punctate signals, such as fluorescently-tagged neurotransmitter receptors and cell adhesion molecules, as well as proteins in other subcellular contexts. By overcoming constraints on time, sample size, cell morphology, and phenotypic space, this work represents a powerful resource for further analysis of synapse biology in C. elegans.

neuroscience↗
bioRxiv2022

Integrating bulk and single cell RNA-seq refines transcriptomic profiles of specific C. elegans neurons.

Neuron-specific morphology and function are fundamentally tied to differences in gene expression across the nervous system. We previously generated a single cell RNA-seq (scRNA-Seq) dataset for every anatomical neuron class in the C. elegans hermaphrodite. Here we present a complementary set of bulk RNA-seq samples for 52 of the 118 canonical neuron classes in C. elegans. We show that the bulk RNA-seq dataset captures both lowly expressed and noncoding RNAs that are not detected in the scRNA-Seq profile, but also includes false positives due to contamination by other cell types. We present an analytical strategy that integrates the two datasets, preserving both the specificity of scRNA-Seq data and the sensitivity of bulk RNA-Seq. We show that this integrated dataset enhances the sensitivity and accuracy of transcript detection and differential gene analysis. In addition, we show that the bulk RNA-Seq data set detects differentially expressed non-coding RNAs across neuron types, including multiple families of non-polyadenylated transcripts. We propose that our approach provides a new strategy for interrogating gene expression by bridging the gap between bulk and single cell methodologies for transcriptomic studies. We suggest that these datasets advance the goal of delineating the mechanisms that define morphology and connectivity in the nervous system.

genetics↗